code: def test_add_indicators_to_all_variables_when_variables_is_none(
      df_na,
  ):
      imputer = AddMissingIndicator(missing_only=False, variables=None)
      X_transformed = imputer.fit_transform(df_na)
      assert imputer.variables_ == [
          "Name",
          "City",
          "Studies",
          "Age",
          "Marks",
          "dob",
      ]
      assert X_transformed.shape == (8, 12)
      assert "dob_na" in X_transformed.columns
      assert X_transformed["dob_na"].sum() == 0
  
file_path: feature_engine/tests/test_imputation/test_missing_indicator.py
imports: import pytest
  from sklearn.pipeline import Pipeline
  from feature_engine.imputation import AddMissingIndicator
label_desc: Use image node_id 2 for calling a global function with example usage: test_add_indicators_to_all_variables_when_variables_is_none(df_na) without return types